Project Team
Student(s)
Calvin Park
Mechanical Engineering
The Pennsylvania State University
Mentor(s)
Department of Mechanical Engineering
Project Video
Project Abstract
A major component of power plant generation in our world today involves the use of turbine blades. The turbine blades work in a very hostile environment with their operating temperature frequently exceeding 1600 OC. Typically, turbine blades are manufactured using conventional methods such as investment casting. These turbines are required to have a single crystal structure in the entire component so that they can withstand the high thermal loading. Manufacturing turbine blades in this fashion are incredibly expensive and time-consuming. These components also have a limited lifespan as they operated in a high thermal stress environment. As the turbine reaches the end of its life cycle, they are simply scrapped as currently there are no known repair methods to restore them. With the advancement of new manufacturing techniques such as additive manufacturing (AM), it is possible to increase the lifespan of a turbine blade by repairing them.
AM processes typically involve numerous process parameters that affect the final deposit quality. Experimental optimization with turbine materials is deemed to be time-consuming and expensive. In order to select suitable process parameters to facilitate the experimental repair process, in this work, a computational framework using Autodesk Netfabb® is created to evaluate the effects process parameters such as laser power, scan speed, and scan pattern on the repair quality for a candidate turbine material system, CMSX-4®. The simulation results are post-processed using visualization software, Paraview to characterize the melt pool dimension and the thermal gradient inside the melt pool. The thermal gradient has a direct impact on the single crystal growth and, hence, by extracting the thermal gradient a direct linkage to single crystal growth as a function of process parameters can be obtained. This project has enabled me to down select the process parameters that I plan on using to fabricate sample specimens when the laboratory opens in Fall. If the experimental trials are successful, the repair method will enable us to reduce both material and energy waste leading to significant carbon footprint reduction.
Project Poster
https://sites.psu.edu/climatedrawdown2020/files/formidable/6/CP-Drawdown-Poster.pdf